Craig W. Reynolds. An evolved, vision-based behavioral model of coordinated group motion. In Meyer and Wilson, editors, From Animals to Animats (Proceedings of Simulation of Adaptive Behaviour). MIT Press, 1992.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....through a 30x30 pixels image (color Z buffer map) In [2] Akeley describes in detail the hardware Z buffer of the IRIS graphics system and gives the formula to calculate the distance of a given pixel to the eye when knowing the projection and the viewpoint transformations. Reynolds [21] more recently described an evolved, vision based behavioral model of coordinated group motion. Tu and Terzopoulos [26] 27] introduced a vision based perception for fishes. Real life is full of different sounds and the addition of music or other sounds in video productions can considerably ....

C.W. Reynolds, An Evolved, Vision-Based Behavioral Model of Coordinated Group Motion, in: Meyer JA et al. (eds) From Animals to Animats, Proc. 2nd International Conf. on Simulation of Adaptive Behavior, MIT Press, 1993.

....as a basis for implementing everyday human behaviour such as visually directed locomotion, handling objects, and responding to sounds and utterances. We first introduced the concept of synthetic vision [ as a main information channel between the environment and the digital actor. Reynolds [ 24 ] more recently described an evolved, vision based behavioral model of coordinated group motion. Xu and Terzopoulos [ 25 26 Also Badler et al. 27 ] reported research on Terrain Reasoning for Human Locomotion. Digital actors should also be equipped with the ability to navigate past obstacles ....

C.W. Reynolds, An Evolved, Vision-Based Behavioral Model of Coordinated Group Motion, in: Meyer JA et al. (eds) From Animals to Animats, Proc. 2nd International Conf. on Simulation of Adaptive Behavior, MIT Press, 1993.

....necessary information from the environment to the virtual human in the problems of path searching, obstacle avoidance, and internal knowledge representation with learning and forgetting characteristics. Visionbased behavioral models have been already described by Renault et al. 37] and Reynolds [38]. In [37] each pixel of the vision input has the semantic information giving the object projected on this pixel, and numerical information giving the distance to this object. So, it is easy to know, for example, that there is a table just in front at 3 meters. With this information, we can ....

Reynolds CW (1993) An evolved, Vision-Based Behavioral Model of Coordinated Group Motion, in: (Meyer JA, Roitblat HL, Wilson SW, eds) From Animals to Animats, Proc. 2nd International Conf. on Simulation of Adaptive Behavior, MIT Press.

....robots) include [178] 157] 105] In addition, techniques inspired by biological evolution have also been used in cooperative robotics. 177] uses a genetic algorithm [66] to evolve neural network controllers for simulated prey creatures that learn a herding behavior to help avoid predators. [138] uses genetic programming [90] to evolve flocking behavior in simulated boids. 2.5. Geometric Problems Because mobile robots can move about in the physical world and must interact with each other physically, geometric problems are inherent to multiple robot systems. This is a fundamental ....

C. Reynolds. An evolved, vision-based behavioral model of coordinated group motion. In Proc. Simulation

....operate autonomously in these environments. These agents must be able to exhibit certain behaviors without user intervention. Various methods for generating higher levels of behavior and movement decisions were investigated first in the pioneering work by Reynolds [19] and then in work by others [8, 27, 18, 3, 14, 20, 9, 25, 13]. AI approaches [8, 11] are capable of generating autonomous behavior, but such techniques typically require complex inferencing mechanisms. This may require considerable computational resources, raising the question of scaling up such systems as the number of independent agents grows, or when ....

C. Reynolds. An evolved, vision-based behavioral model of coordinated group motion. In M. Press, editor, Proc. 2nd International Conf. on Simulation of Adaptive Behavior, 1993.

....certain behaviors autonomously, without user intervention. Among the various methods higher levels of behavior, and movement decisions were investigated first in the pioneering work by Reynolds (Reynolds 1987) and then in work by others (Bates, Loyall, Reilly 1992; Noser Thalmann 1993; Reynolds 1993; Tu Terzopoulos 1994; Noser et al. 1995) AI approaches (Lethebridge C 1989; Funge, Tu, Terzopoulos 1999) are capable of generating autonomous behavior, but typical such techniques require complex inferencing mechanisms. This may require considerable computational resources, raising the ....

Reynolds, C. 1993. An evolved, vision-based behavioral model of coordinated group motion. In Proc. 2nd Int. Conf. on Simulation of Adaptive Behavior.

....of problem domains. Zaera et al. considered possible reasons for their failure. The argument which most convinced them was that real schooling arises through complex interactions, and that their simulations lacked sufficient complexity (their section 5) They cited two promising works: 11 Reynolds (1992) evolution of coordinated group motion in prey animats pursued by a hardwired predator, and Rucker s (1993) ecosystem model in which Boid like animat controllers (or rather their parameters) were evolved. Both of these are moves towards more intrinsic, automatic evolution. The use of ....

....evolution. Notably, Reynolds (1994) of Boids fame worked towards more automatic evolution by coevolving simulated mobile agent controllers which competed with each other in games of Tag. This eliminated the need to design a controller in order to evolve a controller, as in his previous work (Reynolds 1992) mentioned above. 4.2 (No) Emergence via artificial selection From the above discussion, one might imagine our argument to be developing toward the extreme statement that evolutionary emergence is not possible in a system using artificial 12 selection. This is not quite so, although we do argue ....

Reynolds, C. W. (1992). An evolved, vision-based behavioral model of coordinated group motion. In J. A. Meyer, H. Roitblat, and S. Wilson (Eds.), From Animals to Animats 44 2: Proceedings of the Second International Conference on Simulation of Adaptive Behavior (SAB92), pp. 384--392. Cambridge, MA: MIT Press.

.... convinced them was that real schooling arises through complex interactions, and that their simulations lacked su#cient complexity (Zaera et al. 1996, section 5) They cited two promising works: Reynolds evolution of coordinated group motion in prey animats pursued by a hard wired predator (Reynolds, 1992), and Rucker s ecosystem model (Rucker, 1993) in which Boid like animat controllers (or rather their parameters) were evolved. Both of these are moves towards more intrinsic, automatic evolution. The use of coevolutionary models is fast becoming a dominant approach in the adaptive behavior ....

Reynolds, C. W. (1992). An evolved, vision-based behavioral model of coordinated group motion. In Meyer, Roitblat, and Wilson, editors, From Animals to Animats 2: Proceedings of the Second International Conference on Simulation of Adaptive Behavior (SAB92), pages 384--392, Cambridge, MA. MIT Press.

.... adaptive behaviour literature by Webb s work on phonotaxis in crickets and robots [Webb, 1993] Webb, 1994, Webb and Hallam, 1996] and in extremis by the Braitenberg vehicles [Braitenberg, 1984] Arti cial Evolution of Flocking Reynolds has evolved coordinated motion in cloned groups of animats [Reynolds, 1992]. A genetic programming method [Koza, 1992] is used to produce control systems. A candidate controller is copied to 20 visually guided animats placed in a world containing xed obstacles and a preprogrammed predator. Animats die if they touch an obstacle or the predator. The controller is scored ....

....and a preprogrammed predator. Animats die if they touch an obstacle or the predator. The controller is scored over a xed length trial according to an explicit tness function based on the survival of the animats and some style criteria designed by Reynolds to encourage attractive ocking [Reynolds, 1992, p388] Figure 2.4: Apparent but false ocking in an animat simulation. Animats (circles) leave trails for 10 timesteps to indicate direction and speed. Reynolds is looking for (and gets) interesting coordinated motion. The in uence of the predator on evolved behaviour is obscure due to the ....

Reynolds, C. W. (1992). An evolved, vision-based behavioral model of coordinated group motion. In Meyer, J. and Wilson, S., editors, From Animals to Animats (Proceedings of Simulation of Adaptive Behaviour). MIT Press.

.... behaviour literature by Webb s work on phonotaxis in crickets and robots [Webb, 1993] Webb, 1994] Webb and Hallam, 1996] and in extremis by the Braitenberg vehicles [Braitenberg, 1984] Arti cial Evolution of Flocking Reynolds has evolved coordinated motion in cloned groups of animats [Reynolds, 1992]. A genetic programming method [Koza, 1992] is used to produce control systems. A candidate controller is copied to 20 visually guided animats placed in a world containing xed obstacles and a preprogrammed predator. Animats die if they touch an obstacle or the predator. The controller is scored ....

....and a preprogrammed predator. Animats die if they touch an obstacle or the predator. The controller is scored over a xed length trial according to an explicit tness function based on the survival of the animats and some style criteria designed by Reynolds to encourage attractive ocking [Reynolds, 1992, p388] Reynolds is looking for (and gets) interesting coordinated motion. The in uence of the predator on evolved behaviour is obscure due to the additional evolutionary pressure from a complex environment and the arbitrary nature of the tness function. Werner and Dyer, 1992] also evolves ....

Reynolds, C. W. (1992). An evolved, vision-based behavioral model of coordinated group motion. In Meyer, J. and Wilson, S., editors, From Animals to Animats (Proceedings of Simulation of Adaptive Behaviour). MIT Press.

.... convinced them was that real schooling arises through complex interactions, and that their simulations lacked sufficient complexity (Zaera et al. 1996, section 5) They cited two promising works: Reynolds evolution of coordinated group motion in prey animats pursued by a hard wired predator (Reynolds, 1992), and Rucker s ecosystem model (Rucker, 1993) in which Boid like animat controllers (or rather their parameters) were evolved. Both of these are moves towards more intrinsic, automatic evolution. The use of coevolutionary models is fast becoming a dominant approach in the adaptive behavior ....

Reynolds, C. W. (1992). An evolved, vision-based behavioral model of coordinated group motion. In Meyer, Roitblat, and Wilson, editors, From Animals to Animats 2: Proceedings of the Second International Conference on Simulation of Adaptive Behavior (SAB92), pages 384--392, Cambridge, MA. MIT Press.

....learning (done in simulation, as opposed to the works abovewhich were implementedon actual robots) include [Whi91, Tan93, Lit94] 25 [WD92] uses a genetic algorithm [Gol89] to evolve neural network controllers for simulated prey creatures that learn a herding behavior to help avoid predators. Rey92] uses genetic programming [Koz90] to evolve flocking behavior in simulated boids. 26 This distinguishes robots from traditional distributed computer systems in which individual nodes are stationary. Detailed reviews of path planning are found in [Fuj91, Lat91, AO92] Fujimura [Fuj91] views ....

C. Reynolds. An evolved, vision-basedbehavioral model of coordinatedgroup motion. In Proc. Simulation of Adaptive Behavior, 1992.

....A mating event consists of breeding two parse trees to produce two new parse trees, a total of four, and then placing the two most fit of the four in place of the two originally chosen. This is a strongly eleitist mating scheme. Steady state genetic algorithms are described very well by Reynolds [4] and were discovered independently by Syswerda [5] and Whitley [7] We decided to use the steady state algorithm because we are measuring success by computing evolutionary time until a correct answer appears in our population. A steady state algorithm gives much finer time resolution than a ....

Craig Reynolds. An evolved, vision-based behavioral model of coordinated group motion. In Jean-Arcady Meyer, Herbert L. Roiblat, and Stewart Wilson, editors, From Animals to Animats 2, pages 384--392. MIT Press, 1992.

....programmatic behaviors in a domain like the Soccer Server. This paper describes GP and how we used it to evolve coordinated team behaviors and actions for our soccer softbots in RoboCup 97. Genetic programming has been successfully applied many times in the field of multiagent coordination. [Reynolds, 1993] used GP to evolve boids in his later work on flocking and herd coordination. Raik and Durnota, 1994] used GP to evolve cooperative sporting strategies, and [Luke and Spector, 1996] Haynes et al., 1995] and [Iba, 1996] used GP to develop cooperation in predator prey environments and other ....

C. W. Reynolds. An Evolved, Vision--Based Behavioral Model of Coordinated Group Motion. In J.-A. Meyer et al., editors, Proceedings of the Second International Conference on Simulation of Adaptive Behavior. The MIT Press, Cambridge MA, 384--392, 1993.

....have been a number of uses of genetic programming, perhaps inspired by Dawkins biomorphs [Daw86] or Karl Sims panspermia [Sim91] which generate patterns on a computer display. For example [GH97] describes GP being used to make a short single character video. While Reynolds boids technique [Rey92, Rey94b, Rey94a] has been used as a basis for photo realistic imagery of bat swarms in the films Batman Returns and Cliffhanger [Rey96] DFP 94] uses genetic programming to generate sounds and three dimensional shapes. Virtual reality techniques are used to present these to the user. As ....

Craig W. Reynolds. An evolved, vision-based behavioral model of coordinated group motion. In Meyer and Wilson, editors, From Animals to Animats (Proceedings of Simulation of Adaptive Behaviour). MIT Press, 1992.

....is to evolve the controllers, using their ability to perform the desired behavior as a measure of fitness. In these experiments, corridor following behavior is used as a simple test case, representative of the more complex behaviors to which this approach might eventually be applied. Previous work [Reynolds 1993b] has shown that the Genetic Programming Paradigm [Koza 1992] can be used to automatically create control programs which enable a simple moving 2d vehicle to avoid collisions with obstacles by mapping sensory input (range data) into motor output (steering action) In those experiments all fitness ....

....its only means of avoiding collision. These experiments have produced robust control programs capable of corridor following behavior in the presence of noise. Figure 1 shows some examples of successful behavior. Figure 1: Several collision free runs. 2 Related work An early series of experiments [Reynolds 1993b] used Genetic Programming to create reactive controllers for a similar obstacle avoidance task. The fitness test employed a single, precisely repeatable simulation based fitness test. This allowed evolution to take the easy path to discover a program which only solved this one specific control ....

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Reynolds, C. W. (1993) An Evolved, Vision-Based Behavioral Model of Coordinated Group Motion, in From Animals to Animats 2: Proceedings of the Second International Conference on Simulation of Adaptive Behavior (SAB92), Meyer, Roitblat and Wilson editors, MIT Press, Cambridge, Massachusetts, pages 384-392.

No context found.

Craig W. Reynolds. An evolved, vision-based behavioral model of coordinated group motion. In Meyer and Wilson, editors, From Animals to Animats (Proceedings of Simulation of Adaptive Behaviour). MIT Press, 1992.

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Reynolds, C.W., 1993a. An evolved, vision-based behavioral model of coordinated group motion, in: Meyer, J.A., Roitblat, H.L., Wilson, S.W., (Eds.), From Animals to Animats 2: Proc. of SAB92, MIT Press, Cambridge, MA, pp. 384--392.

No context found.

C.W. Reynolds. An evolved, vision-based behavioral model of coordinated group motion. In J.-A. Meyer, H. Roitblat, and S. W. Wilson, editors, From Animals to Animats 2. Proceedings of the Second International Conference on Simulation of Adaptive Behavior (SAB92), pages 384--392. MIT Press, Cambridge, MA, 1993.

No context found.

Craig W. Reynolds. An evolved, vision-based behavioral model of coordinated group motion. In Meyer and Wilson, editors, From Animals to Animats (Proceedings of Simulation of Adaptive Behaviour). MIT Press, 1992.

No context found.

C.W. Reynolds. An evolved, vision-based behavioral model of coordinated group motion. In J.-A. Meyer, H. Roitblat, and S. W. Wilson, editors, From Animals to Animats 2. Proceedings of the Second International Conference on Simulation of Adaptive Behavior (SAB92), pages 384--392. MIT Press, Cambridge, MA, 1993.

No context found.

C.W. Reynolds, An Evolved, Vision-Based Behavioral Model of Coordinated Group Motion, in: Meyer JA et al. (eds) From Animals to Animats, Proc. 2nd International Conf. on Simulation of Adaptive Behavior, MIT Press, 1993.

No context found.

Reynolds CW (1993) An Evolved, Vision-Based Behavioral Model of Coordinated Group Motion, in: Meyer JA et al. (eds) From Animals to Animats, Proc. 2nd International Conf. on Simulation of Adaptive Behavior, MIT Press.

No context found.

C. W. Reynolds. An evolved, vision-based behavioral model of coordinated group motion. In Meyer JA et al., editor, From Animals to Animats, Proc. 2nd International Conf. on Simulation of Adaptive Behavior.MIT Press, 1993.

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C. W. Reynolds. An evolved, vision-based behavioral model of coordinated group motion. In [SAB92].

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